1. Technical Field of the Invention
This invention is related to turbo codes, and more specifically, architecture for iterative processing of a channel of information using a second concatenated turbo code generated from a first turbo code.
2. Description of the Related Art
Digital communications links are used for the efficient and flexible transmission of a wide range of data services. In general, as these services and their supporting networks migrate towards higher rates, and more bursty packet oriented structures, it is important that the physical layer have both access techniques and modulation/coding techniques to efficiently convey this type of data. This is especially important in many applications in which both bandwidth and power are limited resources. Many industry forums and regulatory bodies have concluded that technology advances in power and spectrum efficiency are needed to support the projected use of these services.
It is widely accepted that Forward Error Correction (FEC) is a valuable technique to increase power and spectrum efficiency, and thus will have an important role in these systems. However, the development of FEC with increased coding gain and decreased overhead does have a limit. This limit arises from Shannon's Channel Capacity theorem (published in a 1948 paper entitled “A Mathematical Theory of Communication”) that states that the Bit Error Rate (BER) performance of any rate code will be bounded. This bound is illustrated in FIG. 1, and shows that the maximum coding performance that can be achieved on the antipodal channel for a variety of code rates, e.g., ¼, ⅓, ½, ⅔, and ⅘. No codes can perform better than this theoretical maximum. This also holds for any concatenation of codes.
The task of the code designer then is to develop a codec (an encoder and decoder pair) that exhibits a performance curve that is as close as possible to Shannon's theoretical maximum. However, another implication of the capacity theorem is that the closer the code is to the theoretical maximum, the more complex it will to become to implement.
What is needed is an algorithm that encodes/decodes information bits in a way that approaches the theoretical channel capacity, but is still practical to implement.